Managing excess capacity of database systems in a capacity controlled computing environment

ABSTRACT

Excess capacity available to a database system in a capacity controlled environment can be effectively managed. In particular, excess capacity that is not made available for normal operations of a database system can be used to manage errors, especially situations that may hinder expected performance of the database system. In addition, excess capacity can be used to optimize or further optimize database queries, especially those that meet a criterion (e.g., not fully optimize, not optimized as expected).

BACKGROUND

The term database can refer to a collection of data and/or datastructures typically stored in a digital form. Data can be stored in adatabase for various reasons and to serve various entities or “users.”Generally, data stored in the database can be used by the databaseusers. A user of a database can, for example, be a person, a databaseadministrator, a computer application designed to interact with adatabase, etc. A very simple database or database system can, forexample, be provided on a Personal Computer (PC) by storing data on aHard Disk (e.g., contact information) and executing a computer programthat allows access to the data. The executable computer program can bereferred to as a database program or a database management program. Theexecutable computer program can, for example, retrieve and display data(e.g., a list of names with their phone numbers) based on a requestsubmitted by a person (e.g., show me the phone numbers of all my friendsin Ohio).

Generally, database systems are much more complex than the example notedabove. In addition, databases have been evolved over the years and somedatabases that are for various business and organizations (e.g., banks,retail stores, governmental agencies, universities) in use today can bevery complex and support several users simultaneously by providing verycomplex queries (e.g., give me the name of all customers under the ageof thirty five (35) in Ohio that have bought all items in a list ofitems in the past month in Ohio and also have bought ticket for abaseball game in San Diego and purchased a baseball in the past 10years).

Typically, a Database Management System (DBMS) is provided forrelatively large and/or complex database. As known in the art, a DBMScan effectively manage the database or data stored in a database, andserve as an interface for the users of the database. A DBMS can beprovided as an executable computer program (or software) product as alsoknown in the art.

It should also be noted that a database can be organized in accordancewith a Data Model. Notable Data Models include a Relational Model, anEntity-relationship model, and an Object Model. The design andmaintenance of a complex database can require highly specializedknowledge and skills by database application programmers, DBMSdevelopers/programmers, database administrators (DBAs), etc. To assistin design and maintenance of a complex database, various tools can beprovided, either as part of the DBMS or as free-standing (stand-alone)software products. These tools can include specialized Databaselanguages (e.g., Data Description Languages, Data ManipulationLanguages, Query Languages). Database languages can be specific to onedata model or to one DBMS type. One widely supported language isStructured Query Language (SQL) developed, by in large, for RelationalModel and can combine the roles of Data Description Language, DataManipulation language, and a Query Language.

Today, databases have become prevalent in virtually all aspects ofbusiness and personal life. Moreover, database use is likely to continueto grow even more rapidly and widely across all aspects of commerce.Generally, databases and DBMS that manage them can be very large andextremely complex partly in order to support an ever increasing need tostore data and analyze data. Typically, larger databases are used bylarger organizations. Larger databases are supported by a relativelylarge amount of capacity, including computing capacity (e.g., processorand memory) to allow them to perform many tasks and/or complex taskseffectively at the same time (or in parallel). On the other hand,smaller databases systems are also available today and can be used bysmaller organizations. In contrast to larger databases, smallerdatabases can operate with less capacity. In either case, however, thereis a need for a flexible database environment that can adjust better tothe needs of it users and also allow the capacity of the database tochange as the need of its users change.

In view of the foregoing, techniques for controlling the capacity forcomputing environments or systems that include a database are needed.

SUMMARY

Broadly speaking, the invention relates to computing systems andcomputing environments. More particularly, the invention pertains totechniques for managing the excess capacity of database or databasesystem in a capacity controlled computing environment.

In accordance with aspect of the invention, excess capacity available toa database system in a capacity controlled environment can beeffectively managed. In particular, excess capacity that is not madeavailable for normal operations of a database system can be used tomanage errors, especially situations that may hinder expectedperformance of the database system. By way of example, database queriesthat take longer than expected to complete due to a potential systemerror can be executed using excess capacity. In addition, excesscapacity can be used to optimize or further optimize database queries,especially those that meet a criterion (e.g., not fully optimize, notoptimized as expected).

The invention can be implemented in numerous ways, including, forexample, a method, an apparatus, a computer readable medium, a databasesystem, and a computing system (e.g., a computing device). A computerreadable medium can, for example, include at least executable computerprogram code stored in a tangible or non-transient form. Severalembodiments of the invention are discussed below.

In accordance with one embodiment of the invention, in a computingenvironment, a database system can effectively manage excess capacityand make it available for processing one or more operations includingoperations pertaining to processing one or more database queries and/oroperation pertaining to optimization or further optimization of databaseone or more database queries.

Other aspects and advantages of the invention will become apparent fromthe following detailed description, taken in conjunction with theaccompanying drawings, illustrating by way of example the principles ofthe invention.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will be readily understood by the followingdetailed description in conjunction with the accompanying drawings,wherein like reference numerals designate like structural elements, andin which:

FIG. 1A depicts a computing environment including a capacity managementsystem provided for a database (or a database system) in accordance withone embodiment of the invention.

FIG. 1B depicts a multi-node database system, including a computingcapacity management system in accordance with one embodiment of theinvention.

FIG. 1C depicts a method for controlling capacity of a database systemin accordance with one embodiment of the invention.

FIG. 2 depicts a method for processing data by a database (or databasesystem) in accordance with one embodiment of the invention.

FIG. 3 depicts a method for controlling the capacity of a database (or adatabase system) in accordance with another embodiment of the invention.

FIG. 4A depicts a capacity management system for a database inaccordance with another embodiment of the invention.

FIG. 4B depicts a method for controlling the capacity of a database inaccordance with yet another embodiment of the invention.

FIG. 4C depicts a method for processing one or more database tasks oractivities in accordance with one embodiment of the invention.

FIG. 5 depicts a “closed-loop” capacity and workload management system500 in accordance with one embodiment of the invention.

FIG. 6 depicts in greater detail the regulator in accordance with oneembodiment of the invention.

FIG. 7 depicts in greater detail query (delay) manager in accordancewith one embodiment of the invention.

FIG. 8 depicts in greater detail an exception monitoring in accordancewith one embodiment of the invention.

FIG. 9A depicts in greater detail an exception monitor as a part of aregulator in accordance with one embodiment of the invention.

FIG. 9B depicts a subsystem condition detector and adjuster (SSCDA) anda system condition detector and adjuster (SCDA) in accordance with oneembodiment of the invention.

FIG. 9C depicts an arrangement for handling inputs and outputs to andfrom a SCDA in accordance with one embodiment of the invention.

FIG. 10 depicts a database node of a database system or databasemanagement system (DBMS) in accordance with one embodiment of theinvention.

FIG. 11 depicts a Parsing Engine (PE) in accordance with one embodimentof the invention.

FIG. 12 depicts a Parser in accordance with one embodiment of theinvention.

FIG. 13 depicts a computing environment in accordance with oneembodiment of the invention.

FIG. 14 depicts a method for operating a database or database system inaccordance with one embodiment of the invention

FIG. 15 depicts a method for managing excess capacity of a database ordatabase system in accordance with one embodiment of the invention.

FIG. 16 depicts a method for managing excess capacity of a database ordatabase system in accordance with another embodiment of the invention.

DETAILED DESCRIPTION

As noted in the background section, databases have become prevalent invirtually all aspects of business and personal life. Moreover, databaseuse is likely to continue to grow even more rapidly and widely acrossall aspects of commerce. Generally, databases and DBMS that manage themcan be very large and extremely complex partly in order to support anever increasing need to store data and analyze data. Typically, largerdatabases are used by larger organizations. Larger databases aresupported by a relatively large amount of capacity, including computingcapacity (e.g., processor and memory) to allow them to perform manytasks and/or complex tasks effectively at the same time (or inparallel). On the other hand, smaller databases systems are alsoavailable today and can be used by smaller organizations. In contrast tolarger databases, smaller databases can operate with less capacity. Ineither case, however, there is a need for a flexible databaseenvironment that can adjust better to the needs of it users and alsoallow the capacity of the database to change as the need of its userschange.

Accordingly, techniques for controlling the capacity for computingenvironments or systems that include a database are needed. Inparticular, controlling the capacity of database systems would be veryuseful, especially given the prevalence of the database in variousaspects of business and life in the world today.

Furthermore, it is likely that the use of databases will still continueto grow rapidly to serve an even wider range of entities with widelydiffering needs and requirements. Hence, it would be useful to controlthe capacity of computing environments or systems that include adatabase. In particular, it would be very useful to allow the capacityof a database to change as desired or needed. In other words, it wouldbe very useful to provide a database system that can change its capacityor ability to perform various database related tasks, activities, etc.(or “database work”). For example, the ability to rapidly upgradehardware resources (e.g., number of database nodes and theircorresponding processors) in what may be budget-friendly increments tocustomers or purchasers of a database is highly desirable and useful. Itwould also be useful to provide capacity controlled environment for adatabase system capacity to, for example provide capacity to users,customers and/or purchasers of database as desired or needed (e.g.,providing Capacity on Demand (COD)). It would also be useful to managethe excess capacity (e.g., the capacity not configured for use orregular use by a database system).

Accordingly, techniques for managing the excess capacity of database ordatabase system in a capacity controlled computing environment aredisclosed.

In accordance with aspect of the invention, excess capacity available toa database system in a capacity controlled environment can beeffectively managed. In particular, excess capacity that is not madeavailable for normal operations of a database system can be used tomanage errors, especially situations that may hinder expectedperformance of the database system. By way of example, database queriesthat take longer than expected to complete due to a potential systemerror can be executed using excess capacity. In addition, excesscapacity can be used to optimize or further optimize database queries,especially those that meet a criterion (e.g., not fully optimize, notoptimized as expected).

In accordance with one embodiment of the invention, in a computingenvironment, a database system can effectively manage excess capacityand make it available for processing one or more operations includingoperations pertaining to processing one or more database queries and/oroperation pertaining to optimization or further optimization of databaseone or more database queries.

Embodiments of these aspects of the invention are also discussed belowwith reference to FIGS. 1A-16. However, those skilled in the art willreadily appreciate that the detailed description given herein withrespect to these figures is for explanatory purposes as the inventionextends beyond these limited embodiments.

FIG. 1A depicts a computing environment 100 including a capacitymanagement system 101 provided for a database (or a database system) 102in accordance with one embodiment of the invention. Although not shownin FIG. 1A, it should be noted that the database or database system 102can also include a Data Base Management System (DBMS). Those skilled inthe art will readily appreciate that the capacity management system 101can be provided by hardware and/or software. For example, the capacitymanagement system 101 can be provided as executable code stored on acomputer storage medium (not shown) that can be read and executed by oneor more processors (not shown).

As will be described in more detail below, the capacity managementsystem 101 can control the capacity of the database 102. As such, thecapacity management system 101 can, for example, be operable to change,vary, and/or maintain the capacity of the database 102 in a controlledmanner. Although depicted as a component separate from the database 102,it should be noted that the capacity management system 101 may partiallyor entirely be implemented as a part of the database (or databasesystem) 102 as will be appreciated and readily understood by thoseskilled in the art. In particular, it will be appreciated that thecapacity management system 101 can be provided at least in part in or bya DBMS (not shown in FIG. 1A).

Referring to FIG. 1A, generally, capacity management system 101 can useone or more resources 104 in order to process data or requestsassociated with the database 102. The resources 104 can, for exampleinclude processors, memory, access to various services and functions(e.g., Input and Output (I/O) operations, including reading and writingof the data to and from the database 102).

As will be appreciated by those skilled in the art, the resources 104may be a part of the database 102 or be a part of a larger computingenvironment or system, namely the computing environment 100. Also, thedatabase 102 can include one or more database nodes, each including oneor more processors operable to process data which is typically stored ina computer readable storage medium (e.g., a hard disk). It should benoted that the processor(s) and the computer readable storage medium ofa database node may be a part of the resources 104.

The database 102 may, for example, be a conventional database operableto perform conventional functions. As such, the database 102 can be adatabase system with multiple database nodes. In other words, thedatabase 102 can include multiple database nodes (Node 1 to Node N)where a database node (Node I) can access one or more resources 104(e.g., processors, volatile memory, persistent memory, persistentstorage, Input/output (I/O) operations, communication or networkingcapabilities, Operating System (OS)).

As a multi-node database, each one of the database nodes 1-N can operateand process data independently but in a coordinated manner, which mayallow the database nodes to communicate with a central entity (e.g., adatabase managing component) and/or directly or indirectly with eachother. A multi-node database system is described further below withreference to FIG. 1B in accordance with one embodiment of the invention.

However, referring back to FIG. 1A, generally, the database 102 or oneor more database nodes of the database 102 can access one or moreresources 104 in the computing environment 100 to perform one or moretasks and/or to process data. As known in the art, generally, a resource104 can be a physical or virtual component and may be used to perform orto facilitate performing a task or a computing task (e.g., processing ormanipulating data, reading or writing data, communicating data to aninternal or external component). As such, a resource 104 may be aphysical resource. For example, one or more internal physical componentsof the database 102, or one or more devices connected to the database102 can be computing resource 104 in the computing environment 100. Aresource 104 may also be a virtual resource. For example, various files,network connections and memory areas can be virtual resources 104 thatmay be available to the database 102. As such, a resource 104 can, forexample, include resources or computing resources often used to performcomputing tasks (e.g., one or more general purpose or specializedprocessors, memory, access to I/O operations to read and write data) aswell as various other resources (e.g., hard disk space, Random AccessMemory (RAM), cache memory, and virtual memory, network throughput,electrical power, external devices, external devices).

Generally, a database or database system 102 can be provided by or as asystem or computing system with an associated level of capacity,including computing capacity which can be representative of itspotential to perform tasks. By way of example, for a relatively simplePersonal Computer (PC), the computing capacity of the PC can be closelyrelated to the clock cycle of its processor or as more commonly knownits processing power or speed (e.g., one (1) Giga Hertz (GHZ)). However,more accurately, the computing capacity of a computing system can beclosely related to all of the resources available to the computingsystem, including but not limited to its processor(s), memory, abilityto perform I/O functions, its networking capabilities, storage space).As such, the computing capacity of the database 102 can be closelyrelated to virtually all of the resources 104 available to it in thecomputing environment 100. It should also be noted that capacity of thedatabase 102 does not necessary reflect its actual or current level ofusage. Rather, the capacity of the database 102 is generally related toa maximum level of usage that can be accommodated by the resources 104.

To further elaborate, consider when that database 102 is provided as acomputing system. In that case, when the capacity of the computingsystem is at full capacity or one hundred (100) percent, the computingsystem can be operable up to its maximum potential capacity. This doesnot, however, mean that the computing system has to operate or everreach its capacity or maximum potential. As such, a computing systemmay, for example, be operating at seventy five (75) percent capacityeven though it is operable at full capacity or one hundred (100) percentcapacity when it is determined to reduce its capacity from full capacityto one half (or 50 percent). However, in the example, when the capacityis reduced from full capacity to half or fifty (50) percent, thecomputing system can no longer operate at 75% percent of its fullcapacity (i.e., the level it was operating before its capacity wasreduced from).

To further elaborate, FIG. 1A depicts the controlled capacity of thedatabase 102 and the actual usage of the capacity (i.e., actual usage ofresources 104 by the database system 102) over time. As such, thecapacity of the database 102 can be a cap placed on the extent of usageof the resources 104. In other words, the capacity of the computingenvironment 100 and/or database 102 can be controlled by controlling theextent in which the resources 104 are made available in accordance withone aspect of the invention. Moreover, it will be appreciated that thecapacity management system 101 can control the capacity of the database102 so as to change or vary the capacity over time in a controlledmanner in accordance with another aspect of the invention. This meansthat the capacity management system 101 can effectively change thecapacity of the database system 102 from a first capacity (C1) at a timeT1 to a second capacity (C2) at time T2, which is different than thefirst capacity (C1). In other words, the capacity of the database systemcan be changed or varied at runtime or execution time in a dynamicmanner.

As depicted in FIG. 1A, the computing capacity of the computingenvironment 100 and/or database system 102 can be varied over time.Moreover, the capacity management system 101 can achieve this variationof the computing capacity in a controlled manner, where the currentcomputing capacity may be increased or decreased as desired and/orneeded. This means that the capacity of the database 102 and/orcomputing environment 100 can be controlled on demand to provideCapacity On-Demand, or Capacity on Demand (COD).

As will be described in greater detail, the capacity management system101 can use various techniques in order to effectively change thecapacity of the database 102. By way of example, the capacity managementsystem 101 can be operable to change the effective processing speed (ormaximum processing speed) of one or more processors provided as, oramong, the resources 104. In addition, or alternatively, the capacitymanagement system 101 can, for example, be operable to change theeffective rate in which the processors operate (e.g., by skipping one ormore clock cycles). As another example, access or execution time of oneor more processors provided as or among the resources 104, as well asother various other resources 104 (e.g., access to I/O operations) canbe delayed. In addition, the time, rate and/or duration of access to aresource 104 can be controlled to effectively monitor and limit theextent of access to the resource 104. Techniques for changing thecapacity of the database system 102 are discussed in greater detailbelow.

By in large, the computing capacity of a computing system, which may bemore directly related to its ability (e.g., performing tasks, processingdata) can be a good representative of its overall or general capacity.As such, rather than controlling all the resources 104 representative ofa general capacity which may include resources less directly related toperforming computing tasks (e.g., hard disk capacity, power resource,network capability), controlling the computing capacity by controllingthe resources that are more directly related to performing tasks andprocessing data can be sufficient, especially for database systems thatprimarily function to process data and requests pertaining to datastored in a database. Accordingly, techniques for controlling thecomputing capacity of database system are further discussed below ingreater detail. The techniques are especially suited for computingsystems that primarily function to perform computing tasks (e.g.,database systems, computing systems that primarily function to processdata and/or perform computing tasks).

As noted above, the database or database system 102 (depicted in FIG.1A) can, for example, be a multi-node database system. Moreover, it willbe appreciated that a capacity management system 101 can be provided tocontrol the capacity of a multi-node database system 102. In fact, sucha capacity management system can be provided as a part of a multi-nodedatabase system 102.

To further elaborate, FIG. 1B depicts a multi-node database system 120,including a computing capacity management system 121 in accordance withone embodiment of the invention. It will be appreciated that thecomputing capacity management system 121 can be operable to change thecomputing capacity of multiple database nodes (Nodes 1-N) of thedatabase system 120 at execution time in a controlled and dynamicmanner. This means that the computing capacity management system 121 caneffectively control the computing capacity of the multi-node databasesystem 120 by effectively controlling the computing capacity of one ormore (or all) of the database nodes 1-N when data is being processed byone or more database nodes 1-N of the multi-node database system (e.g.,when database queries are being processed). In other words, capacitymanagement system 121 can effectively control the extent of access toresources 104 by one or more (or all) of the database nodes 1-N of themulti-node database system 120.

It should be noted that the computing capacity management system 121can, for example, depict in greater detail components that can beprovided for the capacity management system 101 shown in FIG. 1A.Specifically, the capacity management system 121 can include a centralcomponent 121A and a node component 121B in accordance with theembodiment depicted in FIG. 1B. The central component 121A of thecomputing capacity management system 121 can be operable to effectivelycontrol the computing capacity of the database system as whole and/orcoordinate or manage the capacity control activities as performedlocally at one or more database nodes 1 to Node N. In contrast, a nodecomponent 121B can primarily control and/or monitor the computingcapacity of a particular database node (i.e., a node I) withoutcontrolling or having knowledge about the manner in which the capacityof any other database nodes, or the capacity of the multi-node databasesystem 120 as a whole, is being controlled.

Generally, the computing capacity management system 121 of themulti-node database system 120 can be operable to obtain (e.g., receive,determine) an overall target capacity for the multi-node database system120 and effectively set and/or change the computing capacity of themulti-node database system 120 to the overall target capacity. Asdescribed in greater detail below, the computing capacity managementsystem 121 can also be operable to maintain the overall capacity for themulti-node database system 120 at an overall target or desired computingcapacity. By way of example, the central component 121A may obtain anoverall target capacity for the multi-node database system 120, andbased on the overall target capacity, determine an individual targetcapacity for a particular database node. Accordingly, the centralcomponent 121A can, for example, be operable to communicate thedetermined individual target capacity of a particular database node(Node I) to its respective node component 121-BI. The node component121-BI can, in turn, set and/or maintain the computing capacity of thedatabase node I to the determined individual target capacity ascommunicated by the central component 121A. Other database nodes canoperate in a similar manner to set and maintain their node capacity at atarget capacity. As a result the overall target computing capacity forthe database system can be achieved.

For example, a target overall computing capacity which is half (or 50percent) of the full computing capacity can be received as input by thecomputing capacity management system 121 as a target computing capacityfor the database 120. In the example, the central component 121A maydetermine to change the computing capacity of each one of the databasenodes (Node 1-Node N) from their current capacity, which may be at fullcomputing capacity to half computing capacity. As such, centralcomponent 121A may be operable to communicate with all of the nodecomponents (121B1-121-BN) to effectively cause them to change theircapacities from full to half computing capacity.

Alternatively, central component 121A may determine to set thecapacities of the individual database nodes (Node 1-Node N) to variouslevels individually to achieve the desired overall target capacity. Assuch, central component 121A may cause the capacity of a first databasenode to be changed form full to half capacity, while the computingcapacity of a second database node may be increased from twenty five(25) percent to fifty (50) percent, the computing capacity of a thirddatabase node may be set to seventy (70) percent computing capacity, thecomputing capacity of a third database node may be set to thirty (30)percent computing, and so on, in order to achieve a desired overallcapacity, namely, half or fifty (50) percent overall capacity for themulti-node database system 120.

As another example, if one or more database nodes of the multi-nodedatabase system 120 fail, the capacity of the database nodes that arestill operable can be adjusted to compensate for the loss of one or morenodes in order to still achieve an overall capacity for a database. Inthe example, the capacity of the database nodes can be readjusted whenall database nodes become operable again.

To further elaborate, FIG. 1C depicts a method 150 for controllingcapacity of a database system in accordance with one embodiment of theinvention. Method 150 can, for example, be performed by the capacitymanagement system 101 (shown in FIG. 1A) or the computing capacitymanagement system 121 (shown in FIG. 1B).

Referring to FIG. 1C, optionally, it can be determined (152) whether tochange the capacity of a database system from its current capacity. Asthose skilled in the art will readily appreciate, the determination(152) can, for example, represent a design or programming choice and/orcan be made based on input and/or one or more criteria (e.g.,determining a need to change the capacity to handle a high priorityrequest or performing system upgrade, receiving a target capacity asinput, receiving a command to change the capacity). In effect, method150 can wait for a determination (152) to change the capacity of thedatabase system unless it is determined (154) to end the method 150. Assuch, the method 150 can, for example, end as a result of receivinginput, system shutdown, etc. However, if it is determined (152) tochange the capacity of the database system, the capacity of the databasesystem can be changed (156) from it current capacity to a differentcapacity. The capacity of the database system can, for example, bechanged by causing the usage capacity of at least one of the resourcesto be changed from a current usage capacity to a different usagecapacity. Thereafter, method 150 can proceed to determine whether tochange the capacity of the database system in a similar manner as notedabove. Method 500 can end if it is determined (154) to end it.

As noted above, a capacity management system (e.g., capacity managementsystem 101 depicted in FIG. 1A, computing capacity management system 121depicted in FIG. 1B) can be operable to change or vary the capacity ofthe database system at execution time or runtime, in a dynamic manner inaccordance with aspect of the invention.

To further elaborate, FIG. 2 depicts a method 200 for processing data bya database (or database system) in accordance with one embodiment of theinvention. Method 200 can, for example, be performed by the capacitymanagement system 101 (shown in FIG. 1A) or the computing capacitymanagement system 121 (shown in FIG. 1B).

Referring to FIG. 2, initially, the computing capacity of a database isset (202) to a first capacity (e.g., a first computing capacity). Asnoted above, the capacity of a database can, for example, be set to aparticular value by setting (e.g., changing, adjusting, limiting) theusage capacity of one or more resources (e.g., processors, access to I/Ooperations) associated with the database. Next, the database can processdata and various database operations can be performed. In other words,conventional database operations can be performed. Specifically, it canbe determined (204) whether a database request or query has beenreceived. Accordingly, processing of a database request can be initiated(206). In effect, method 200 can continue to process data and performdatabase operations unless it is determined (208) to end processing ofthe data and the performing database operations. The database operationscan, for example, end as a result of a system shutdown or receivingauthorized input. As such, the method 200 can end if it is determined(208) to end the processing of data and performing database operations.

However, it should be noted that while the data is being processedand/or database operations are being performed by the database, it canbe determined (210) whether to change the capacity of the database. Thedetermination (210) can, for example, be made based on input indicativeof change, or based on one or more criteria (e.g., one or more systemconditions, periodic adjustments, need to meet service goals). If it isdetermined (210) to change the capacity of the database, it can also bedetermined (212) whether to determine a capacity (i.e. different or newcapacity) for the database.

It should be noted that a different capacity can be received as input sothere may not be a need to determine (214) a capacity for the database.However, if it is determined (212) to determine a capacity for thedatabase, a capacity which is different than the first capacity can bedetermined (214) for the database. It will be appreciated by thoseskilled in the art, a capacity for the database can be determined basedon one or more criteria (e.g., the extent in which excess capacity isneeded to perform maintenance, periodic adjustment, past usage and/oranticipated usage, amount of money paid for capacity).

In any case, if it determined (210) to change the capacity of thedatabase from the first capacity to a different capacity, regardless ofwhether a capacity is determined (212) or not, the capacity of thedatabase is set (214) to a second capacity, different than the firstcapacity (i.e., higher or lower than the first capacity). The capacityof the database can be set to the second capacity, for example, byaffecting the usage capacity of one or more resources associated withthe database (i.e., by effectively increasing or decreasing the usagecapacity or extent of allowed usage of one or more resources associatedwith the database).

After, the capacity of the database has been effectively changed bysetting (214) the capacity to a second capacity, the method 200 canproceed determine (210) whether to change the capacity of the database.As result, the capacity of the database can be changed (216) in adynamic manner at runtime or execution time, while the data is beingprocessed and database operations are being performed by the database(i.e., the database is operational and/or active) in a similar manner asdiscussed above. Method 200 ends if it determined (208) to the end theprocessing of data and database operations.

As noted above, it can be determined whether to change the currentcapacity of a database (or database system) based on input indicative ofchange, or one or more criteria (e.g., one or more system conditions,periodic adjustments, need to meet service goals). By way of example, itcan be determined to extend or increase the current capacity of adatabase in order to meet a system requirement (e.g., a Service LevelAgreement (SLA) requiring high priority database queries to be processedwithin a determined time period, system maintenance or update). As such,it can, for example, be determined to allow excess capacity beyond atarget capacity (e.g., fifty (50) percent) in order to meet an SLA or toallow a system update. It should also be noted that excess systemcapacity can also be measured and accounted (e.g., billed) in accordancewith one aspect of the invention.

To further elaborate, FIG. 3 depicts a method 300 for controlling thecapacity of a database (or a database system) in accordance with anotherembodiment of the invention. Method 300 can, for example, be performedby the capacity management system 101 (shown in FIG. 1A) or thecomputing capacity management system 121 (shown in FIG. 1B).

Referring to FIG. 3, initially, a target capacity for the database canbe obtained (302). The target capacity can, for example, be received asinput or determined based on one or more criteria (e.g., capacityselected and/or paid for by a user and/or customer of a database, typesand/or number of database requests currently pending). It should benoted that the target database capacity can, for example, berepresentative of an overall target capacity for a database or adatabase system (e.g., a multi-node database system), or a specifictarget capacity for one or more database nodes of a multimode database).After the target capacity of the database is obtained (302), thecapacity of the database or a portion of the database (e.g., one or moredatabase nodes of a multimode database) can be set (304) to the targetsystem capacity.

As will be described in greater details below, the capacity of at leasta part of the database can be set (304) based on a target capacity byusing one or a combination of various techniques. By way of example, oneor more database tasks or activities can be regulated with respect tothe access to one or more resources of the database based on the targetcapacity. In other words, the extent to which one or more database tasksor activities can access one or more resources of the database (e.g.,access to processor for execution time, access to I/O operations) can becontrolled based on a target capacity in order to effectively set thecapacity of at least a portion of the database to the target capacity.As another example, the effective processing rate and/or clock rate ofone or more processors of the database can be set based on the targetcapacity.

In any case, in addition to setting the capacity of at least a portionof the database based on the target capacity, monitoring can beinitiated (306) if it has not been initiated already. This monitoringcan, for example, include monitoring the usage of one or more resourcesand/or one or more system conditions (e.g., monitoring execution of oneor more database tasks and resources consumed by them, monitoring forconditions that are programmed to trigger change in the capacity of thedatabase).

After the monitoring has been initiated (306) it is determined (308)whether to change the capacity of at least a portion of the databasefrom its current capacity (e.g., whether to change the capacity of adatabase from a target capacity under which the database is configuredto operate under normal circumstances). It should be noted that thedetermination (308) can be made based on the monitoring data obtained asa result of the monitoring that has been initiated (306) and after atleast a portion of the database has been set (304) or configured tooperate at a target capacity. By way of example, monitoring (306) of oneor more system conditions can indicate a need to increase the capacity.As such, it can be determined (308) to allow the database to exceed itstarget capacity at least for a period of time. Generally, if it isdetermined (308) to change the capacity of at least a portion of thedatabase, the capacity of at least one portion of the database can beincreased or decreased (310). By way of example, the overall capacity ofa multi-node database system can be increased from its target capacity,fifty (50) percent, to seventy five (75) percent in order to meet a needor a requirement.

It should be noted that capacity and/or actual usage can optionally bemonitored and stored (e.g., measured and recorded) based on themonitoring (306) of the tasks and the resources consumed by them. Assuch, it can optionally be determined (312) whether to monitor (e.g.,measure) the capacity and/or actual usage of the capacity provided.Consequently, the capacity and/or actual usage of the capacity of adatabase can be monitored and stored (314). By way of example, capacityused beyond a target capacity (or excess capacity) can be measured basedon monitoring the usage of one or more resources consumed by databasetasks or activities. Usage of resources in an excess of the targetcapacity can, for example, be billed at a cost or as an additional costbeyond the target capacity. After the capacity of at least a portion ofdatabase has changed (312) it can be determined (316) whether to set thecapacity of at least a portion of the database back to the targetcapacity. Accordingly, the capacity of at least a portion of thedatabase can be set (304) to the target capacity again and the method300 can proceed in a similar manner as discussed above.

However, if it is determined (316) not to set the capacity of at least aportion of the database to the target capacity, the method 300 canproceed to determine whether to change the capacity of at least aportion of the database. In effect, method 300 can wait for adetermination (308) to change the capacity of at least a portion of thedatabase unless it is determined (318) to end the method 300, forexample, based on input provided by a database administrator, or whenthe system is to be shut down.

More Specific Techniques for Controlling Resources of a Database

As noted above, the capacity of database can be controlled byeffectively controlling the usage capacity of one or more resourcesassociated with a database in accordance with one aspect of theinvention. In particular, access to the computing resources of adatabase can be controlled in order to effectively control the computingcapacity of a database. Typically, a task (e.g., a database query)requires access to various computing resources (e.g., access to aprocessor or execution time, access to I/O operations including readingdata stored in a database and writing data to the database). In otherwords, access to resources required by a database can be effectivelyregulated in accordance with one aspect of the invention. It will beappreciated that a capacity management system can effectively regulateaccess to resources of a database in accordance with one embodiment ofthe invention.

To further elaborate, FIG. 4A depicts a capacity management system 400for a database in accordance with one embodiment of the invention. Thecapacity management system 400 can represent in a greater detail thecomponents that can be provided for the capacity management system 101(shown in FIG. 1A) or the computing capacity management system 201(shown in FIG. 1B). It should be noted that one or more components ofthe capacity management system 400 can, for example, be provided ascentral component for a multi-node database and/or can be provided as anode component for a particular database node of a multi-node database.

Referring to FIG. 4A, the capacity management system 400 can include aregulator (or a usage regulator) 402 operable to effectively regulateaccess to various resources R1-RN. More specifically, regulator 402 canregulate access to resources R1-RN when the database is activelyprocessing data and requests (e.g., when queries made by one or moreusers of a database are being processed by the database). Data andrequests can be processed by a Database Management System (DBMS) (e.g.,a Relational Database Management System (RDBMS) 404. Conceptually, DBMS404 can be provided over an Operating System (O.S.) 407. DBMS 404 caneffectively request access to resources provided and/or under thecontrol of the OS 407 which may include one or all of the resourcesR1-RN. Typically, resources R1-RN can include storage for storing dataused by the DBMS 404, as well as one or more processors (e.g., CentralProcessing Units (CPUs).

As suggested by FIG. 4A, one or more of the resources R1-RN can be partof the O.S. 407. By in large, DBMS 404 and O.S. 407 can be considered tocollectively make at least a significant part of a database or databasesystem that could also include storage for storing data (not shown).Conceptually, the DBMS 404 may generate various database tasks DBT1-DBTNas data or requests are processed or database operations are beingeffectively managed by the DBMS 404. For example, in response to variousdatabase queries made by one or more users of the database, a number ofdatabase tasks DBT1-DBTN can be generated.

Typically, completion of a database task DBTI requires execution timeand access to one or more I/O operations in order to complete.Generally, the regulator 402 can regulate the database tasks DBT1-DBTNat least with respect to access to the resources R1-RN.

The regulator 411 can, for example, include or cooperate with, ascheduler that effectively regulates or controls the amount of time aparticular task DBTI is to wait before it can access a particularresource RJ and/or the amount of access time a particular task DBTI haswith respect to a resource RJ when access is granted. The scheduler caneffectively schedule the access time of the database tasks DBT1-DBTNwith respect to the resources R1-RN based on a target capacity. As such,when the database is regulated to be at full capacity, the regulator 402may schedule a particular task DBTI to execute as soon as possible andfor as long as possible, of course, in consideration of other databasetasks, especially those that may have a higher priority. However, if thecapacity of the database is regulated by the regulator 402 to be at halfof its full capacity, the regulator 402 may, for example, cause anadditional delay (i.e., relative to delay that can be experienced atfull capacity) before a particular task DBTI is executed and/or is givenaccess, for example, to an I/O resource, such as a read or write to thedatabase. Similarly, at half of full capacity, the regulator 402 mayallow a particular task DBTI to execute for a shorter time than it wouldhave if the database was regulated (or allowed to operate) at fullcapacity and/or may allow a shorter access time to I/O operationsrequired by a particular database task DBTI. As a result, a task DBTImay, for example, take a significantly longer time (e.g., about two (2)times longer) to complete when the database is at half capacity than itwould if the database was operating at full capacity.

Referring to FIG. 4A again, it should also be noted that the regulator402 can receive input from a capacity (or capacity tuning) manager 404which can effectively manage the capacity of the database by providinginput indicative of a target or desired capacity under which theregulator 402 is to regulate access to the resources R1-RN. The capacitymanager 405 can determine a target or desired capacity for the regulator402 at least partially based on the monitoring data or informationprovided by a monitor 406. The monitor 406 can monitor usage of theresources R1-RN, as well as the progress of the database tasks DBT1-DBTNin order to provide the monitoring data to the capacity manager 405.

More specifically, the monitor 406 can monitor usage of the resourcesR1-RN by the database tasks DBT1-DBTN, at least some of which may alsobe effectively regulated by the regulator 402. It should be noted thatthe monitor 406 can also be operable to determine the overall usage ofthe resources R1-RN, for example, by obtaining the information from theO.S. 407. This means that the monitor 406 can be operable to monitorusage of the resources R1-RN by activities that may not be directlyrelated to the DBMS 404 or activities that may not be directlycontrolled or regulated by the regulator 402 (e.g., system tasks, OStasks, OS dump, Gateway, applications outside the database system,Network applications, such as TCP/IP, CLI, MTDP, MOSI). Thus, themonitor 406 can determine the usage of the resources R1-RN by thedatabase tasks DBT1-DBTN, as well as the overall usage of the resourcesR1-RN, which also includes usage by tasks or activities other than thedatabase tasks DBT1-DBTN (e.g., non-database tasks). As such, themonitor 406 can provide the regulator 402 and/or the capacity manager405 with resource usage information indicative of the extent of usage ofthe resources R1-RN by each or all of the database tasks DBT1-DBTN, aswell as the extent of total usage of the resources R1-RN by all tasksand activities, including those that may not be directly related to theDBMS 404 and/or controllable by the regulator 402.

In addition, monitor 406 can monitor the progress of a database taskDBTI and/or estimate time required to complete a database DBTI task. Themonitoring data provided by the monitor 406 can affect the regulationactivities of the regulator 402, either directly or indirectly, via thecapacity manager 405.

Referring to FIG. 4A yet again, it should also be noted that aninterface 410 (e.g., a User Interface (UI), a Graphical User Interface(GUI)) may be optionally provided by or for the capacity managementsystem 400. The interface 410 can be operable to receive input (e.g., atarget capacity) and provide output (e.g., current over all systemcapacity, system capacity of an individual database node, general oroverall resource usage information, overall resource usage informationpertaining to database tasks or activities, one or more specificresource usage information pertaining to one or more database tasks).

To further elaborate, FIG. 4B depicts a method 420 for controlling thecapacity of a database in accordance with yet another embodiment of theinvention. Method 420 can, for example, be performed by the capacitymanagement system 400 depicted in FIG. 4A.

Referring to FIG. 4B, initially, a target capacity for a database isobtained (422). The target capacity can, for example, be received asinput or determined based on one or more criteria (e.g., capacityselected and/or paid for by a user and/or customer of the database,types and/or quantity of data requests currently pending). It should benoted that the target database capacity can, for example, berepresentative of an overall target capacity for a database or adatabase system (e.g., a multi-node database), or a target capacity forone or more particular database nodes of a multimode database).

Next, based on the target capacity, one or more database tasks oractivities (e.g., one or more database queries, I/O operations) areregulated (424) with respect to their access to one or more resourcesassociated with the database (e.g., access to a processor or executiontime, access to a read or write operation). By way of example, a targetcapacity of half of full capacity can result in causing a determineddelay in execution of some or all of the queries currently pending, aswell as any additional queries received later after the capacity is setor regulated to be half of its full capacity. This delay can, forexample, be made in direct proportion to the target capacity and can besignificantly longer than the delay that would be experienced when thedatabase is regulated at the full capacity. It will be appreciated thatthe delay can, for example, be caused by scheduling the databaseactivities based on the target capacity, as will be described in greaterdetail below.

Referring back to FIG. 4B, method 420 ends after one or more databasetasks or activities are regulated (424) with respect to their access toone or more resources associated with the database based on the targetcapacity.

As noted above, a scheduling technique can be used to cause delays inprocessing of the data and/or performing tasks by a database. The delayscan be made in proportion to a target or desired capacity for thedatabase in accordance with one aspect of the invention.

To elaborate further, FIG. 4C depicts a method 430 for processing one ormore database tasks or activities in accordance with one embodiment ofthe invention. Method 430 can, for example, represent in greater detailoperations that may be performed to regulate (424) one or more databasetasks based on target capacity in accordance to the method 420 depictedin FIG. 4B.

Referring to FIG. 4C, initially, it is determined (432) whether there isat least one database task or activity to process. In effect, method 430can wait for a determination (432) that one or more database tasks oractivities are to be processed. By way of example, it can be determined(432) that one or more database queries have been submitted forprocessing by the database.

If it is determined (432) that there is at least one database task oractivity to process, the current target capacity of the database isobtained (434). In addition, one or more database tasks or activitiesare scheduled for execution and/or for access to other computingresources (e.g., access to an I/O operation) based on the current targetcapacity of the database. Typically, the scheduling (436) causesrelatively longer delays for target capacities that are relatively lowerwith respect to full capacity. As such, a target capacity of, forexample, fifty (50) percent can cause relatively longer delays incompletion of one or more database tasks or activities than the delaysthat would be caused by a target capacity of seventy five (75) percent,but a target capacity of twenty five (25) percent could cause asignificantly longer delay than the delay when the target capacity is atfifty (50) percent, and so on.

After the one or more database tasks or activities are scheduled (436),it is determined (438) whether at least one database task or activity isstill pending. In other words, it can be determined (438) whether atleast one database task or activity has not completed. If it isdetermined (438) that no task or activity is still pending, the method430 can effectively wait (432) for one or more tasks or activities to bereceived for processing. However, if it is determined (438) that leastone database task or activity is still pending, it can be determined(440) whether to adjust the scheduling of one or more tasks oractivities that are still pending. By way of example, if the targetcapacity of the database has changed, it can be determined to rescheduleone or more tasks or activities. As a result, execution of one or moretasks can be rescheduled and/or access to other computing resources canbe rescheduled based on the current target capacity which is differentthan the target capacity at the time access to resources was initiallyscheduled for the one or more tasks or activities. As such, if itdetermined (440) to adjust the scheduling of one or more pending tasksor activities, the current target capacity can be obtained (434) and oneor more tasks or activities that are pending can be rescheduled based onthe current target capacity in a similar manner as discussed above.

Closed-Loop Capacity Management Architecture

In accordance with yet another aspect of the invention, a “closed-loop”capacity management architecture can be provided. As such, it will beappreciated that a capacity management system 400 (depicted in FIG. 4A)can, for example, be provided using or in a “closed-loop” capacitymanagement architecture in accordance with one embodiment of theinvention. The “closed-loop” capacity management architecture can, forexample, be similar to the closed-loop workload management architecturedescribed in U.S. Pat. No. 7,657,501, entitled: “Regulating the WorkLoad of a Database System,” by “Brown et al.” and filed on Aug. 10,2004, which is hereby incorporated by reference herein in its entiretyand for all purposes. As described in greater detail in the U.S. Pat.No. 7,657,501, entitled: “Regulating the Work Load of a DatabaseSystem,” a system provided in “closed-loop” workload managementarchitecture can satisfying a set of workload-specific goals.

With respect to managing capacity, a system that can satisfy capacitygoals or requirements in a “closed-loop” capacity managementarchitecture will be described below in accordance with one embodimentof the invention. It should be noted that workload management andcapacity management can be provided together in a system to allowmeeting workload and capacity goals and requirements in accordance withanother aspect of the invention. Since it may be more instructive todiscuss a “closed-loop” system that can manage both workload andcapacity of a database, a “closed-loop” capacity and workload managementsystem is discussed below for the sake of comprehensiveness. However, aswill be readily understood by those skilled in the art, it is notnecessary to manage both capacity and workload of the database as eachof these features can be provided separately even though it may bedesirable to provide both of these features for some applications.

As noted in U.S. Pat. No. 7,657,501, entitled: “REGULATING THE WORK LOADOF A DATABASE SYSTEM,” an automated goal-oriented workload managementsystem can support complex workloads and can self-adjust to varioustypes of workloads. Major operational phases can include: 1) assigning aset of incoming request characteristics to workload groups, assigningthe workload groups to priority classes, and assigning goals (calledService Level Goals or SLGs) to the workload groups; 2) monitoring theexecution of the workload groups against their goals; 3) regulating(adjusting and managing) the workload flow and priorities to achieve theSLGs; 4) recommending adjustments to workload definitions (e.g. bysplitting or merging workload definitions) in order to better isolatethe subset of the workload that requires different workload managementthan the remainder of the original workload; and 5) correlating theresults of the workload and taking action to improve performance.

The performance improvement can be accomplished in several ways: 1)through performance tuning recommendations such as the creation orchange in index definitions or other supplements to table data, or torecollect statistics, or other performance tuning actions, 2) throughcapacity planning recommendations, for example increasing system power,3) through utilization of results to enable optimizer adaptive feedback,and 4) through recommending adjustments to SLGs of one workload tobetter complement the SLGs of another workload that it might beimpacting. Recommendations can either be enacted automatically, or after“consultation” with the database administrator (“DBA”).

FIG. 5 depicts a “closed-loop” capacity and workload management system500 in accordance with one embodiment of the invention. Referring toFIG. 5, an administrator 403 can provide a GUI for defining rules 409that can, for example, include capacity management rules, as well asworkloads and their SLGs, and other workload or capacity managementrequirements. The administrator 403 accesses data in logs 407, includinga query log and receives input including capacity and performancerelated inputs. The administrator 403 can be a primary interface for theDBA. The administrator can also establish rules 409, including capacityand workload rules, which can be accessed and used by other componentsof the closed-loop capacity management and workload management system500.

A monitor 411 can effectively provide a top level dashboard view and theability to drill down to various details of overall and individualizedcomponent capacity at various times, as well as workload groupperformance such as aggregate execution time, execution time by request,aggregate resource consumption, resource consumption by request, etc.Such data is stored in the query log and other logs 407 available to themonitor 411. The monitor 411 also includes processes that initiate theperformance improvement mechanisms listed above and processes thatprovide long term trend reporting, which may include providingperformance improvement recommendations. Some of the monitor 411functionality may be performed by a regulator 415 which can monitor 411capacity and workloads, for example, by using internal messaging system.The regulator 415 can dynamically adjust system settings includingcapacity and/or projects performance issues and can either alert thedatabase administrator (DBA) or user to take action, for example, bycommunication through the monitor 411, which is capable of providingalerts, or through the exception log, providing a way for applicationsand their users to become aware of, and take action on, actions taken bythe regulator 415. Alternatively, the regulator 415 can automaticallytake action by deferring requests or executing requests with theappropriate priority to yield the best solution given requirementsdefined by the administrator 403.

FIG. 6 depicts in greater detail the regulator 415 in accordance withone embodiment of the invention. The regulator 415 can effectivelyregulate processing of requests based on current capacity and/orworkload of a database by dynamically monitoring the capacity andworkload characteristics using rules or other heuristics based on pastand current performance of the system that guide two feedbackmechanisms. It can do this before the request begins execution and atperiodic intervals during query execution. Prior to query execution, thecurrent capacity can be considered. Further, the workloadcharacteristics of the query can be examined (e.g., an incoming requestcan be examined to determine in which workload group it belongs based oncriteria).

As shown in FIG. 6, the regulator 415 can receive one or more requests,each of which can be assigned by an assignment process (block 605) to aworkload group and, optionally, a priority class, in accordance with theworkload rules 409 a. The assigned requests can then be passed to aquery (delay) manager 610. In addition, capacity rules and/or input 409b can be passed to the query (delay) manager 610. In general, the query(delay) manager 610 monitors the workload performance compared to thesystem capacity and/or the workload rules and either allows the requestto be executed immediately or holds it for later execution, as describedbelow. If the request is to be executed immediately, the query (delay)manager 610 places the request in the priority class bucket 620 a-scorresponding to the priority class to which the request was assigned bythe administrator 405. A request processor under control of a priorityscheduler facility (PSF) 625 selects queries from the priority classbuckets 620 a-s, in an order determined by the priority associated witheach of the buckets, and executes it, as represented by the processingblock 630 on FIG. 6.

It should be noted that the query (delay) manager 610 and/or requestprocessor under control of a priority scheduler facility (PSF) 625 canindividually or collectively be operable to effectively delay processingof a request based on a current, a desired, or a target capacity. Therequest processor 625 can also monitor the request processing and reportthroughput information, for example, for each request and for eachworkgroup, to an exception monitoring process 615. The exceptionmonitoring process 615 can compare the throughput with the workloadrules 409 and can store any exceptions (e.g., throughput deviations fromthe workload rules) in the exception log/queue. In addition, theexception monitoring process 615 can provide system resource allocationadjustments to the request processor 625, which can adjust systemresource allocation accordingly, e.g., by adjusting the priorityscheduler weights. Further, the exception monitoring process 615provides data regarding the workgroup performance against workload rulesto the query (delay) manager 610, which can use the data to determinewhether to delay incoming requests, depending on the workload group towhich the request is assigned.

As shown in FIG. 6, the system provides two feedback loops, indicated bythe circular arrows shown in the drawing. The first feedback loopincludes the request processor 625 and the exception monitoring process615. In this first feedback loop, the system monitors on a short-termbasis the execution of requests to detect deviations greater than ashort-term threshold from the defined service level for the workloadgroup to which the requests were defined. If such deviations aredetected, the DBMS is adjusted, e.g., by adjusting the assignment ofsystem resources to workload groups. The second feedback loop includesthe query (delay) manager 610, the request processor 625 and theexception monitoring process 615. In this second feedback loop, thesystem monitors on a long-term basis to detect deviations from theexpected level of service greater than a long-term threshold. If itdoes, the system adjusts the execution of requests, e.g., by delaying,swapping out or aborting requests, to better provide the expected levelof service. Note that swapping out requests is one form of memorycontrol in the sense that before a request is swapped out it consumesmemory and after it is swapped out it does not consume memory. Whilethis is the preferable form of memory control, other forms, in which theamount of memory dedicated to an executing request can be adjusted aspart of the feedback loop, are also possible.

FIG. 7 depicts in greater detail query (delay) manager 610 (also shownin FIG. 6) in accordance with one embodiment of the invention. The query(delay) manager 610 receives an assigned request as an input. Acomparator 705 determines if the request should be queued or releasedfor execution. It does this based on the current or input capacityand/or by determining the workload group assignment for the request andcomparing that workload group's performance against the workload rules,provided by the exception monitoring process 615. For example, thecomparator 705 may examine the concurrency level of requests beingexecuted under the workload group to which the request is assigned.Further, the comparator may compare the workload group's performanceagainst other workload rules. If the comparator 705 determines that therequest should not be executed, it places the request in a queue 710along with any other requests for which execution has been delayed. Thecomparator 705 continues to monitor the workgroup's performance againstthe capacity and/or workload rules and when it reaches an acceptablelevel, it extracts the request from the queue 710 and releases therequest for execution. In some cases, it may not be necessary for therequest to be stored in the queue to wait for workgroup performance toreach a particular level, in which case it is released immediately forexecution. Once a request is released for execution it is dispatched(block 715) to priority class buckets 620 a-s, where it will awaitretrieval by the request processor 625.

FIG. 8 depicts in greater detail an exception monitoring 615 inaccordance with one embodiment of the invention. Exception monitoring615 receives throughput information from the request processor 625. Aworkload performance to capacity and/or workload rules comparator 805compares the received throughput information to the capacity rulesand/or workload rules and logs any deviations that it finds in theexception log/queue 510. The capacity rules can effectively defineperformance for a workload at various capacities. The comparator 805 canalso generate the workload performance against capacity and workloadrules information which can be provided to the query (delay) manager610. To determine what adjustments to the system resources arenecessary, the exception monitoring process calculates a ‘performancegoal index’ (PGI) for each workload group (block 810), where PGI isdefined as the observed average response time (derived from thethroughput information) divided by the response time goal (derived fromthe capacity and/or workload rules). Because it is normalized relativeto the goal, the PGI is a useful indicator of performance that allowscomparisons across workload groups. The exception monitoring process canadjust the allocation of system resources among the workload groups(block 815) using various techniques. For example, one technique is tominimize the maximum PGI for all workload groups for which defined goalsexist. As another example, is to minimize the maximum PGI for thehighest priority workload groups first, potentially at the expense ofthe lower priority workload groups, before minimizing the maximum PGIfor the lower priority workload groups. These techniques can bespecified by a DBA in advance through the administrator. An indicationin the form of a system resource allocation adjustment is transmitted tothe request processor 625. By seeking to minimize the maximum PGI forall workload groups, the system treats the overall workload of thesystem rather than simply attempting to improve performance for a singleworkload. In most cases, the system will reject a solution that reducesthe PGI for one workload group while rendering the PGI for anotherworkload group unacceptable. This approach means that the system doesnot have to maintain specific response times very accurately. Rather, itonly needs to determine the correct relative or average response timeswhen comparing between different workload groups.

FIG. 9A depicts in greater detail an exception monitor 615 as a part ofa regulator 415 in accordance with one embodiment of the invention.Exception monitor 615 includes a subsystem condition detector andadjuster (SSCDA) 5105 and a system condition detector and adjuster(SCDA) 5110. As shown in FIG. 9A, in one example system there is oneSCDA 5110 for the entire system. In some example systems, one or morebackup SCDAs (not shown) are also provided that will operate in theevent that SCDA 5110 malfunctions.

As shown in FIG. 9B, there can be one SSCDA 5105 per dispatcher.However, more than one SSCDA 5105 per dispatcher can be provided. Inaddition, some systems may have only one dispatcher per parsing engine,although this is not a limitation of the concept described herein.Further, in some systems each parsing engine may run on a single node oracross multiple nodes. In some example systems, each node will include asingle parsing engine. Thus, for example, there may be one SSCDA perAMP, one per parsing engine, or one per node.

Returning to FIG. 9A, the SCDA monitors and controls resourceconsumption at the system level, while the SSCDA monitors and controlsresource consumption at the subsystem level, where in some examplesystems, a subsystem corresponds with a single dispatcher. Somesubsystems may correspond to a share of a dispatcher. Further, asubsystem may correspond to more than one dispatcher. Each SSCDAmonitors and controls, in a closed loop fashion, resource consumptionassociated with a single subsystem. An SSCDA monitors throughputinformation that it receives from the request processor 625 and comparesthat performance information to the workload rules 409. The SSCDA thenadjusts the resource allocation in the request processor 625 to bettermeet the workload rules.

The SCDA receives system conditions, compares the conditions to theworkload rules, and adjusts the system resource allocations to bettermeet the system conditions. For convenience, FIG. 9A shows the SCDAreceiving inputs from and sending outputs to the request processor 625.In another exemplary system, the inputs and outputs to and from the SCDAare handled as described below with respect to FIG. 9C.

Generally, the SSCDA provides real-time closed-loop control oversubsystem resource allocation with the loop having a fairly broadbandwidth. The SCDA provides real-time closed-loop control over systemresource allocation with the loop having a narrower bandwidth. The SCDAprovides real-time closed-loop control over system resource allocationwith the loop having a narrower bandwidth. Further, while the SSCDAcontrols subsystem resources and the SCDA controls system resources, inmany cases subsystem resources and system resources are the same. TheSCDA has a higher level view of the state of resource allocation becauseit is aware, at some level as discussed with respect to FIG. 9C, of thestate of resource allocation of all subsystems, while each SSCDA isgenerally only aware of the state of its own resource allocation. Asystem may include some resources that are shared at a system level.Such resources would be truly system resources controlled by the SCDA.

One example of the way that the SCDA 5110 may monitor and control systemresource allocations is illustrated in FIG. 9C. The SSCDAs are arrangedin a tree structure, with one SSCDA (the root SSCDA 5305) at the top ofthe tree, one or more SSCDAs (leaf SSCDAs, e.g. leaf SSCDA 5310) at thebottom of the tree, and one or more intermediate SSCDAs (e.g.intermediate SSCDA 5315) between the root SSCDA and the leaf SSCDAs.Each SSCDA, except the root SSCDA 5305, has a parent SSCDA (i.e. theimmediately-higher SSCDA in the tree) and each SSCDA, except the leafSSCDA, has one or more child SSCDA (i.e. the immediately lower SSCDA inthe tree). For example, in FIG. 9C, SSCDA 5315 is the parent of SSCDA5310 and the child of SSCDA 5320.

In the example shown in FIG. 9C, the tree is a binary tree. It will beunderstood that other types of trees will fall within the scope of theappended claims. Further, while the tree in FIG. 9C is symmetrical,symmetry is not a limitation. The SCDA 5110 gathers system resourceinformation by broadcasting to all SSCDAs a request that they reporttheir current resource consumption. In one example system, each SSCDAgathers the information related to its resource consumption, as well asthat of its children SSCDAs, and reports the compiled resourceconsumption information to its parent SSCDA. In one example system, eachSSCDA waits until it has received resource consumption information fromits children before forwarding the compiled resource consumptioninformation to its parent. In that way, the resource consumptioninformation is compiled from the bottom of the tree to the top. When theroot SSCDA 5305 compiles its resource consumption information with thatwhich is reported to it by its children SSCDAs, it will have completeresource consumption information for the SSCDAs in the system. The rootSSCDA 5305 will report that complete information to the SCDA. The SCDAwill add to that information any resource consumption information thatis available only at the system level and make its resource allocationadjustments based on those two sets of information.

In another exemplary system, each of the SSCDAs communicates itsresource consumption information directly to the SCDA 5110. The SCDA5110 compiles the information it receives from the SSCDAs, adds systemlevel resource consumption information, to the extent there is any, andmakes its resource allocation adjustments based on the resulting set ofinformation.

There are at least two ways by which the SCDA 5110 can implement itsadjustments to the allocation of system resources. The first,illustrated in FIG. 9A, is for the SCDA 5110 to communicate suchadjustments to the request processor 625. The request processor 625implements the adjustments to accomplish the resource allocationadjustments.

Alternatively, the SCDA 5110 can communicate its adjustments to theSSCDAs in the system, either directly or by passing them down the treeillustrated in FIG. 53. In either case, the SSCDAs incorporate theSCDA's resource allocation adjustments in the subsystem resourceallocation adjustments that it sends to the request processor 625.

Capacity Management for Multi-Node, Parallel Database Systems

The techniques described above are especially suitable for multi-node,parallel databases, including those that use a massively parallelprocessing (MPP) architecture or system. To further elaborate FIG. 10depicts a database node 1105 of a database system or database managementsystem (DBMS) 1000 in accordance with one embodiment of the invention.The database system 1000 can, for example, be provided as a TeradataActive Data Warehousing System. FIG. 10 depicts an exemplaryarchitecture for one database node 1105 ₁ of the DBMS 100 in accordancewith one embodiment of the invention. The DBMS node 1105 ₁ includes oneor more processing modules 1110-N connected by a network 1115, thatmanage the storage and retrieval of data in data-storage facilities 1120_(1-N). Each of the processing modules 1110-N represent one or morephysical processors or virtual processors, with one or more virtualprocessors running on one or more physical processors.

For the case in which one or more virtual processors are running on asingle physical processor, the single physical processor swaps betweenthe set of N virtual processors. For the case in which N virtualprocessors are running on an M-processor node, the node's operatingsystem schedules the N virtual processors to run on its set of Mphysical processors. If there are four (4) virtual processors and four(4) physical processors, then typically each virtual processor would runon its own physical processor. If there are 8 virtual processors and 4physical processors, the operating system would schedule the eight (8)virtual processors against the four (4) physical processors, in whichcase swapping of the virtual processors would occur. Each of theprocessing modules 1110 _(1-N) manages a portion of a database stored ina corresponding one of the data-storage facilities 120 _(1-N). Each ofthe data-storage facilities 1120 _(1-N) can includes one or more storagedevices (e.g., disk drives). The DBMS 1000 may include additionaldatabase nodes 1105 _(2-O) in addition to the node 1105 ₁. Theadditional database nodes 1105 _(2-O) are connected by extending thenetwork 1115. Data can be stored in one or more tables in thedata-storage facilities 1120 _(1-N). The rows 1125 _(1-z) of the tablescan be stored across multiple data-storage facilities 1120 _(1-N) toensure that workload is distributed evenly across the processing modules1110 _(1-N). A parsing engine 1130 organizes the storage of data and thedistribution of table rows 1125 _(1-z) among the processing modules 1110_(1-N). The parsing engine 1130 also coordinates the retrieval of datafrom the data-storage facilities 1120 _(1-N) in response to queriesreceived, for example, from a user. The DBMS 1000 usually receivesqueries and commands to build tables in a standard format, such as SQL.

In one implementation, the rows 1125 _(1-z) are distributed across thedata-storage facilities 1120 _(1-N) by the parsing engine 1130 inaccordance with their primary index. The primary index defines thecolumns of the rows that are used for calculating a hash value. Thefunction that produces the hash value from the values in the columnsspecified by the primary index is called the hash function. Someportion, possibly the entirety, of the hash value is designated a “hashbucket”. The hash buckets are assigned to data-storage facilities 1120_(1-N) and associated processing modules 1110 _(1-N) by a hash bucketmap. The characteristics of the columns chosen for the primary indexdetermine how evenly the rows are distributed.

Referring to FIG. 10, it should be noted that a capacity management nodecomponent 1002 can be provided as a separate entity (or component, ormodule) or can be at least partially implemented in the parsing engine1130. In addition, a capacity management central component 1004 can beprovided as a central component that can effectively coordinate and/ormanage the capacity of the DBMS 1000.

In one exemplary system, the parsing engine 1130 is made up of threecomponents: a session control 1200, a parser 1205, and a dispatcher1210, as shown in FIG. 11. The session control 1200 provides the logonand logoff function. It accepts a request for authorization to accessthe database, verifies it, and then either allows or disallows theaccess. When the session control 1200 allows a session to begin, a usermay submit a SQL request, which is routed to the parser 1205. Regardingthe dispatcher 1210, it should be noted that some monitoringfunctionality for capacity and workload management may be performed by aregulator (e.g., regulator 415). The Regulator can monitor capacity andworkloads internally. It can, for example, do this by using internalmessages sent from the AMPs to the dispatcher 1210. The dispatcher 1210provides an internal status of every session and request running on thesystem. It does this by using internal messages sent from the AMPs tothe dispatcher 1210. The dispatcher 1210 provides an internal status ofevery session and request running on the system. As such, at least partof a capacity management system (capacity management 1250) can beprovided by the dispatcher 1210 which operates as a capacity andworkload enhanced dispatcher in order to effectively manage capacityand/or workload in the DBMS 1000.

As illustrated in FIG. 12, the parser 1205 interprets the SQL request(block 1300), checks it for proper SQL syntax (block 1305), evaluates itsemantically (block 1310), and consults a data dictionary to ensure thatall of the objects specified in the SQL request actually exist and thatthe user has the authority to perform the request (block 1305). Finally,the parser 1205 runs an optimizer (block 1320), which generates theleast expensive plan to perform the request.

System conditions that can be considered by DBMS can, for example,include: Memory—the amount of system and subsystem memory currentlybeing used. It is possible that the system will include some memory thatis shared among all of the subsystems. AMP worker tasks (AWT)—the numberof available AWTs. An AWT is a thread or task within an AMP forperforming the work assigned by a dispatcher. Each AMP has apredetermined number of AWTs in a pool available for processing. When atask is assigned to an AMP, one or more AWTs are assigned to completethe task. When the task is complete, the AWTs are released back into thepool. As an AMP is assigned tasks to perform, its available AWTs arereduced. As it completes tasks, its available AWTs are increased. FSGCache—the amount of FSG cache that has been consumed. The FSG cache isphysical memory that buffers data as it is being sent to or from thedata storage facilities. Arrival Rates—the rate at which requests arearriving. Arrival rate can be broken down and used as a resourcemanagement tool at the workload basis. Co-existence—the co-existence ofmultiple types of hardware. Skew—the degree to which data (and thereforeprocessing) is concentrated in one or more AMPs as compared to the otherAMPs. Blocking (Locking)—the degree to which data access is blocked orlocked because other processes are accessing data. Spool—the degree ofconsumption of disk space allocated to temporary storage. CPU—the numberof instructions used per second. I/O—the datablock I/O transfer rate.Bynet latency—the amount of time necessary for a broadcast message toreach its destination.

The techniques for communication between the SCDA 5110 and the SSCDAscan, for example, be accomplished by a single process running across allof the nodes and all of the AMPS, by multiple processes, where eachprocess executes on a separate AMP, or by processes that can run on morethan one, but not all, of the AMPs. “Process” should be interpreted tomean any or all of these configurations.

Since the SCDA 5110 has access to the resource consumption informationfrom all SSCDAs, it can make resource allocation adjustments that aremindful of meeting the system workload rules. It can, for example,adjust the resources allocated to a particular workload group on asystem-wide basis, to make sure that the workload rules for thatworkload group are met. It can identify bottlenecks in performance andallocate resources to alleviate the bottleneck. It can remove resourcesfrom a workload group that is idling system resources. In general, theSCDA 5110 provides a system view of meeting workload rules while theSSCDAs provide a subsystem view.

Managing Errors (e.g., Scheduling Mistakes) and Performance Issues in aCapacity Controlled Environment

As noted above, capacity of a system and/or a database operating in thesystem can be controlled in a dynamic and/or automatic manner. Inparticular, the capacity of a database or database system can becontrolled in a dynamic and/or automatic manner, for example, using oneor more of the techniques noted above. By way of example, a databasesystem or Data Base Management System (DBMS) can dynamically adjust a“throttle” for access to resources, based on time periods or otherevents. In addition, virtually, any resource, including, for example,disk space, disk I/O, and memory can be controlled by using, forexample, a delay mechanism because accessing a resource can beeffectively delayed and/or a resource (e.g., a portion of disk space, aprocessor) can be rendered effectively inaccessible and/or inoperable.

In an environment where capacity is dynamically controlled (e.g., a CODenvironment), resources can be effectively “rented” by a customer, forexample, during anticipated periods of heavy demand in accordance withone or more of the techniques noted above. In addition, a CODarchitecture provided in accordance with the techniques noted above thatallows use or temporarily use excess and/or additional capacity orresources to handle various situations, including, for example, errorsand/or system-identified exceptions (e.g., performance problems).

In other words, a COD enforcement mechanism can be provided that allowscontrolled use of excess of capacity for a number of desired situations.For example, a COD enforcement mechanism can be provided, by anautomated DBMS in accordance with one or more of the techniques notedabove. As such, a DBMS can conceptually or logically partition resourcesor system resources into what can be considered to be “regular” capacityor pools of resources (e.g., paid resources) and excess capacity or“COD-only” capacity (e.g., unpaid resources) including pools ofresources that are not part of the regular capacity, where the DBMS caneffectively prevent tasks (or operations or work), especially databasework, from using the COD-only pools. However, the DBMS can effectivelyallow some tasks to access the COD-only capacity under one or moreconditions or situations, for example, when explicit permission has beengranted for a task to access a COD-only pool or access resource capacityassigned to be COD-only. In case of a parallel architecture noted above,those skilled in the art will readily appreciate that COD-only poolscan, for example, include spool space, file system cache, CPU, etc. TheCOD-only pools can, for example, be included in a configuration for eachAMP virtual processor, as will also be readily appreciated by thoseskilled in the art.

It is noted that using the COD-only pools (or COD-only resources) torespond to a wide class of performance issues may not be an idealsolution for all situations. However, it will be appreciated that usingthe COD-only resources to address errors, including resource estimationerrors and resources estimation inaccuracies, can be useful at least insome situations, especially when a certain level of performance isdesigned and/or promised to be delivered to a customer. In the realworld, especially when operating large and complex database systems,some classes of performance problems may be due to an error, viewed bycustomers as “bugs,” for which there may not be a graceful remedyreadily available. In such cases, customers will often report a problemincident that might be very costly for a database vendor to investigateand repair immediately. For this class of problems, the most costeffective solution for both parties (vendor and customer) may be to atleast temporarily use the excess capacity of a COD system to alleviatethe performance issue.

In accordance with one aspect of the invention, excess capacityavailable in a capacity controlled database system can be used when acondition or a trigger occurs. Such a condition or trigger can, forexample, be caused by what may be considered to be an error (e.g., abug) or deviation in the system. In situations that an error degradesperformance, excess capacity can be used to alleviate the performanceissues allowing a database system to perform as expected despite errorconditions that may occur from time to time.

In the context of a capacity management system or subsystem describedabove, resource usage can be dynamically controlled in a system thatincludes a database. More specifically, a capacity management systemcan, for example, be provided by one or more query scheduling featuresthat rely on an estimation of resource usage from a query optimizer. Inaddition, one or more runtime monitoring features can detect “negative”system performance conditions so that corrective action can be taken.

For example, for queries with a high estimated resource usage, where“high” can, for example, be defined by a user (user defined rules), ascheduler can delay execution of the queries until a period of lowsystem activity and/or effectively throttle or limit the number of suchqueries that can run concurrently. Monitoring features can thenperiodically measure the overall resource contention, as well as theresource usage of individual queries. If contention or excessive use isdetected, it will adjust the relative priority of certain queries toensure service level goals are still met. As a result, one or moreselected queries (e.g., “run-away queries”) may even be aborted.However, it will be appreciated that such queries need not be aborted topreserve the performance of the system. Instead, excess capacity can beused to effectively deal with such situations to allow completion of oneor more selected queries (e.g., “run-away queries”) without adverselyaffecting the performance of the database system.

Queries that may be problematic can be identified based on one or morecharacteristics in accordance with another aspect of the invention. Forexample, one or more of the following characteristic can be defined anddetected for a request or query made from a database.

(i) Consumption beyond a determined amount (or an excessive amount) ofone or more resources (e.g., spool space, file system cache, or CPU).The determined amount can, for example, be defined by one or moreresource rules defined by a user, database administrator, system ordefault rules, determined dynamically based on one or more currentsystem conditions and/or events.

(ii) Inaccurate resource estimates made by a Query Optimizer forresources needed to complete a request or query made from a database.Generally, in such case, an accurate estimation would have resulted indelaying or delaying further the execution of the request or query.

(iii) Assignment of confidence greater than low by a Query Optimizer,implying that the necessary information (e.g., statistics) was availablefor resource estimation.

(iv) Current availability of sufficient spool or cache in the COD-onlypool to satisfy the resource needs that are now more accurately known atruntime.

The above exemplary characteristics can, for example, represent“expensive” queries that were improperly scheduled for execution as aresult of inaccurate resource estimates made by the query optimizer. Arequest or query made from the database that meets one or moreconditions above and/or is consistent with or occurs at one or moreconditions or events noted above (e.g., current availability ofsufficient spool or cache) can be considered a “problematic” query thatmay be processed using the excess capacity of database operating in acapacity controlled environment.

As generally known in the art, even the most sophisticated queryoptimizers can occasionally make such mistakes. These mistakes can bedue to the inherent limitations of current SQL optimizer technology,which relies on summary statistics to estimate the selectivity ofpredicates (WHERE clause conditions). Conventionally, the availablecorrective actions to take against such queries (run-away queries)include lowering their CPU priority or aborting them, neither of whichmay be ideal or palatable to users. Lowering the CPU priority rarelyprovides immediate relief to overall system resource contention andaborting a query may be too severe.

In accordance with another aspect of the invention, excess capacity oradditional COD-only resources can be provided to allow execution ofrequests or queries based on one or more criteria (e.g., quires that cancause contention of resources in an unacceptable manner). By way ofexample, additional COD-only resources can be provided for execution ofrun-away queries based on one or more of the exemplary conditions notedabove. As a result, problematic queries, such as, “run-away” queriesneed not be aborted as their execution can be continued without furthercontention with other queries competing for the “regular” (e.g., paidfor) resources in the current configured capacity (e.g., half of thefull capacity). The COD-only resources can be provided on a temporarybasis and can be measured.

For example, in the case of excessive spool space, the remainingoperations of the identified run-away query can be granted access toCOD-only spool space for all subsequent spool requests. As anotherexample, in the case of excessive cache usage, the executing operationsof the identified run-away query can be granted access to COD-only cachefor all subsequent cache requests.

To elaborate even further, consider a multi-way join query with anexecution plan requiring a large intermediate binary join result to bestored in a spool file. If the query optimizer significantlyunderestimates the required spool size, the scheduler may mistakenlyschedule it for immediate execution on a busy system where availablespool is already low. After a monitoring component detects that thequery is using significantly more spool than anticipated, the query canbe detected as a run-away query. As a result, COD-only spool space canbe made available by the monitor and/or another component of a DBMS forthe remainder of the query's execution. As another example, consider acustomer query whose chosen execution plan involves a hash joinalgorithm that requires the inner table (or spool) to fit entirelywithin cache. If the optimizer grossly underestimates the size of theinner table, the scheduler may mistakenly execute the query when theavailability of cache is insufficient. Once the monitoring componentrealizes that the query requires significantly more cache thananticipated, it could make the COD-only cache available for theremainder of the hash join operation.

It should be noted that if the execution of a run-away query can becompleted by temporarily using excess COD-only resources, theperformance of other queries running in the regular (paid) portion ofthe system could be improved as result of less resource contention.Because these corrective actions can happen automatically by actionstaken by a DBMS in accordance with one embodiment of the invention,end-users or customers need not be unaware of any performance issue asthe DBMS can resolve the performance issues with requiring input fromend-users or customers.

Also, to prevent occurrence of the same or similar issues in the future,a DBMS can be configured to gather relevant information for theCOD-usage event in accordance with one embodiment of the invention. Inaddition, the DBMS can be configured to report such issues, for example,to customer support as a non-critical incident. It will be appreciatedthat the use of COD-only pool when a problematic or performance issue(e.g., run-away queries) arises allows investigation of such problem ina non-crises mode where further improvements can be made, for example,to a query optimizer, a query scheduler, etc.

Query Optimization in a Capacity Controlled Environment

As noted above, capacity of a system and/or a database operating in thesystem can be controlled in a dynamic and/or automatic manner inaccordance with the techniques of the invention disclosed above. Inparticular, the capacity of a database or database system can becontrolled in a dynamic and/or automatic manner, for example, using onethe techniques noted above. Further, COD-only capacity or pools ofresources (COD-only pools) can be provided to process one or moreselected database requests and queries in accordance with techniquesdiscussed in the previous section to manage errors and performanceissues.

In accordance with yet another aspect of the invention, COD-onlycapacity (or COD-only pool of resources) can be provided for queryoptimization or to further optimize query plans. By way of example, anadditional phase of query optimization may be performed in COD-onlycapacity (or pool). It may not be feasible to perform this additionalphase of query optimization using just the normal capacity (i.e., byusing just the normal resource pool) due to time and resourceconstraints. More specifically, additional optimization can, forexample, be performed on selected cached or stored query plans that havealready undergone through standard optimization.

As will readily be appreciated by those skilled in the art, the solutionspace of alternative query plans for large complex SQL queries can bevery large, and hence standard optimization may not perform anexhaustive search. On the other hand, performing a “full optimization”could consume too many CPU resources and negatively impact the responsetime of the query. A significant drawback to standard optimization(e.g., a pruned search) is that in some cases the performance of thechosen sub-optimal plan may not achieve the customer's Service LevelGoal (SLG) for that query.

It will also be appreciated that using excess resource capacity of asystem in a capacity controlled system (e.g., COD-only pools of a CODsystem) to perform additional optimization can result in finding moreefficient execution plans, thereby enhancing system performance.Additional optimization can be performed as a background optimizationfor a query without hindering the execution of other queries beingexecuted on the normal pool or resources available in the configured orcontrolled capacity.

In view of the foregoing, it will be readily apparent that a capacitymanagement system can allow using excess capacity for optimization ofquery plans in accordance with one embodiment of the invention. Thecapacity management system can, for example, periodically examineoptimized plans. The optimized plans can, for example, reside within aParsing Engine request cache and a delay queue in a system noted above,or can be stored on disk for a database engine that supports compiledquery plans stored on disk, etc.

In any case, one or more selected criteria can be applied to identifyplans whose performance is likely to be improved with additionaloptimization. Such criteria, can for example, include (a) plans whoseestimated time does not achieve the query's defined SLG, (b) expensiveplans whose estimated elapsed time or resources consumed exceeds aconfigurable threshold (e.g., default of ten (10) minutes elapsed time),or (c) highly complex queries identified as those whose number ofexecution operations or steps exceeds a configurable threshold (e.g.,default is >20 steps). When identified, the selected queries can, forexample, be re-submitted to the SQL Parsing Engine along with a special“further optimize” designation, whereby the assigned PE task can bescheduled to run in the excess COD-only portion of the system with, forexample, an assigned low CPU priority.

Queries labeled as “further optimize” need not be subject to the normalsearch space pruning heuristics used by an Optimizer, thereby allowing arelatively more complete/exhaustive optimization to take place. Suchtasks can continue to run in the background until, for example, one ofthe following events occurs: (1) the associated plan being improved uponis removed from the cache or delay queue, (2) an improved plan is foundthat meets the query's required SLG and is cheaper than currently cachedor delayed plan, or (3) the optimization process runs to fullcompletion. Upon occurrence of event numbered (2) or (3) the identifiedbest plan is used to replace the original optimized plan that currentlyexists in the cache or delay queue for that query. The plan can bemarked as “fully optimized” to avoid subsequent attempts to optimize itfurther.

It is noted that an additional optimization process can operate withoutregard to an original optimization process and hence may be duplicatinga portion of the optimization already performed. However, duplicationmay be acceptable since this additional optimization can be performed atlow priority in the background in accordance with the techniques of theinvention. It should be noted that for query optimizers that accept aninitial plan, “seeding” can be used to “seed” a further-optimizationprocess with the best plan from the original optimization, as will beappreciated by those skilled in the art. Not only the “seeding” canensure that the newly identified best plan is at least as good asbefore, “seeding” can also be used by the plan selection logic to helpnarrow and guide the search. Generally, the process of continuallytrying to improve the efficiency of cached or delayed plans usingoptimizer tasks running on the unused capacity of the system can in turnimprove the performance of running queries.

Managing Excess Capacity of a Database

As noted above, excess capacity can be effectively managed for adatabase or a database system in a capacity controlled computingenvironment. To further elaborate, FIG. 13 depicts a computingenvironment 440 in accordance with one embodiment of the invention.Referring to FIG. 13, the computing environment 440 includes a databasesystem 442 and multiple resources R1-RN, at least some of which can bepart of the database system 442. As those skilled in the art willreadily know, the database system 442 can be operable to store data in adatabase (not shown separately) effectively provided by the databasesystem 442. The database system 442 can access at least one of theresources R1-RN to process data associated with the database.

Moreover, the database 442 can also be operable to regulate work (e.g.,database tasks or activities). By way of example, the database system442 can regulate access or extent of access made by one or more databasetasks to one or more of the resources R1-RN. As such, the databasesystem 442 can, for example, include a capacity management system 101operable to regulate one or more database tasks or activities withrespect to access or extent of access to the resources R1-RN.

Typically, in the database system 442, regulation of database work, suchas, various database tasks or activities (e.g., database requests andqueries) is relatively more useful. As such, database system 442 can beconfigured to regulate at least some work (e.g., non-database work, suchas, system tasks or activities) but some tasks, activities, oroperations (e.g., a non-database task or activity) may not be regulatedin the database system 442. This work can, for example, be regulated bya database management 101 which can be provided in accordance with thetechniques described above.

In effect, the capacity management system 101 can configure and/orcontrol the capacity of the database system 442 so that a desired or atarget capacity below the full capacity of the database system 442 canbe achieved and/or maintained. As a result, excess capacity can beavailable for use but be made effectively inaccessible to the databasesystem 442.

It will be appreciated that in accordance with the embodiment depictedin FIG. 13, the excess capacity, which can remain effectively unusedand/or inaccessible by the database system 442, can be made available bythe capacity management system 101 to the database system 442 forvarious purposes, including error handling and optimization (or furtheroptimization) of execution of database queries. As such, the capacitymanagement system 101 can include an excess-capacity management system441 operable to effectively manage the excess capacity of the databasesystem 442.

Specifically, the excess-capacity management system 441 can determinewhether to allow excess capacity available to the database system 442 tobe used to perform one or more operations and allow or deny use ofexcess capacity accordingly. The determination of whether to allowexcess capacity to be used can be made based on various criteria,including, for example, when there is perceived need to handle an errorcondition (e.g., “run-away” query). As another example, it can bedetermined to allow the use of excess capacity when there is a perceivedneed to further optimize a query (e.g., when: (a) plans whose estimatedtime does not achieve the queries' defined SLG, (b) expensive planswhose estimated elapsed time or resources consumed exceeds aconfigurable threshold or (c) highly complex queries identified as thosewhose number of execution operations or steps exceeds a configurablethreshold).

It should be noted that the excess-capacity management system 441 can beoperable to allow only one or more selected operations to use the excesscapacity, for example, by allowing only the selected operation(s) to usea particular resource or use the resource in a manner that would exceedthe allotted use of the resource in accordance with the configured(limited) capacity made available to the database system 442. As aresult, a selected operation can be allowed access to a resource notnormally available or be granted use of a resource in a manner thatwould not be normally allowed (e.g., less access delay time, longeraccess time).

It should be noted that the excess-capacity management system 441 can beoperable during the processing of database requests and when thedatabase system 442 is active to determine whether to allow excesscapacity available to the database system 442 to be used to perform oneor more operations and allow or deny use of excess capacity accordingly.In other words, excess-capacity management system 441 can manage excesscapacity for the database system 442 in a dynamic manner at runtime orat execution time.

To further elaborate, FIG. 14 depicts a method 1400 for operating adatabase or database system in accordance with one embodiment of theinvention. Method 1400 can, for example, be performed by theexcess-capacity management system 441 depicted in FIG. 13.

Referring to FIG. 14, initially, a database system is initiated (1402)with capacity below its full capacity. In other words, the databasesystem is configured to operate at a limited capacity with at least aportion of the capacity being made effectively inaccessible to thedatabase. When the database system is operational, it is determined(1404) whether to allow use of excess capacity to perform one or moreoperations associated with the database system. By way of example, itcan be determined (1404) whether to allow an error condition to beeffectively handled using excess capacity, or whether to furtheroptimize a query. If it is determined (1404) to allow use of the excesscapacity, one or more operations can be allowed (1406) to use excesscapacity. By way of example, a query may be processed or furtheroptimized using excess capacity. On the other hand, if it is determined(1404) not to allow excess capacity to be used, use of excess capacityis denied. In effect, the method 1400 can continue to determine (1404)whether to allow use of excess capacity while the database system isoperational until it is determined (1408) to end the operations of thedatabase system, for example, as a result of a system shutdown.

FIG. 15 depicts a method 1500 for managing excess capacity in a capacitycontrolled database system in accordance with one embodiment of theinvention. Method 1500 can, for example, be performed by theexcess-capacity management system 441 depicted in FIG. 13.

Referring to FIG. 15, initially, it is determined (1502) whether adatabase query is received. In effect, method 1500 can wait to receive adatabase query for processing. If it determined (1502) that a databasequery has been received, the processing and monitoring of the processingof the query is initiated (1504).

Next, based on the monitoring of the processing of the query, it isdetermined (1506) whether there is a performance issue that merits useof excess capacity. By way of example, it can be determined (1506)whether completion of execution of a database query would hinder systemperformance. As a result, a query can be processed (1508) using excesscapacity available to the database system if it is determined (1506)that there is performance issue that merits use of the excess capacity.Otherwise, the query is not allowed to use excess capacity and would beprocessed (1510) using only the configured or allotted capacity (limitedcapacity).

It should be noted that during the processing of a database query, itcan be determined (1506) to use the excess capacity until it isdetermined (1512) that the processing of the query has completed.However, the database query may be aborted if it is determined (1514) toabort the query prior to the completion of the processing, for example,if use of the excess capacity is not desirable or feasible. Accordingly,if it determined (514) to abort the query, an error can be output(1516). However, it should also be noted that in accordance with themethod 1500, processing of queries can be completed using the excesscapacity at least for some, if not all, of the queries that wouldconventionally just be aborted. Method 1500 ends after the completion(514) of the processing of the query or after an error is output (1516).

FIG. 16 depicts a method 1600 for managing excess capacity in a capacitycontrolled database system in accordance with another embodiment of theinvention. Method 1600 can, for example, be performed by theexcess-capacity management system 441 depicted in FIG. 13.

Referring to FIG. 16, initially, it is determined (1602) whether tooptimize (or further optimize) a database query. In effect, method 1600can wait for a determination (1602) to optimize a database query. If itis determined (1602) to optimize a database query, the optimization ofthe database query is initiated (1604) and it is determined (1606)whether to use excess capacity available to optimize or further optimizethe database query. The excess capacity is available to the databasesystem but is not allotted for normal database operations. Accordingly,excess capacity can be used (1606) to optimize or further optimize thedatabase query, if it is determined (1606) to use excess capacity.Otherwise, the database query can be optimized or further optimized(1607) using only the allotted or configured capacity (i.e., excesscapacity is not used to optimize the database query.

It should be noted that during the optimization of a database it can bedetermined (1606) to use excess capacity and excess capacity may be usedafter optimization is performed using only allotted or configuredcapacity. Furthermore, it is possible to stop usage of excess capacityfor optimization of the database query and/or resume usage of excesscapacity after it has been stopped. Method 1600 end after it isdetermined (1612) to end the optimization of the database query (e.g.,when it determined that an optimal plan has been achieved and/or it isnot feasible or desirable to further optimize the query).

It should also be noted that in accordance with the techniques of theinvention, more expansive and thorough optimization can be performedusing excess capacity which may not be feasible in conventional systems.In addition, the techniques of the invention provide elegant andgraceful solutions that allow overcoming query scheduling mistakes whichare, by in large, inherent to the limitations of the estimationtechnologies.

Additional techniques related to controlling the capacity of a databasesystem are further discussed in the following two (2) U.S. PatentApplications which are both hereby incorporated by reference herein forall purposes: (i) U.S. patent application Ser. No. 13/249,922 entitled:“regulating capacity and managing services of computing environments andsystems that include a database,” by DOUGLAS P. BROWN et al., and (ii)U.S. patent application Ser. No. 13/250,006 entitled: “Managing capacityof computing environments and system that include a database,” by JohnMark Morris et al.

The various aspects, features, embodiments or implementations of theinvention described above can be used alone or in various combinations.The many features and advantages of the present invention are apparentfrom the written description and, thus, it is intended by the appendedclaims to cover all such features and advantages of the invention.Further, since numerous modifications and changes will readily occur tothose skilled in the art, the invention should not be limited to theexact construction and operation as illustrated and described. Hence,all suitable modifications and equivalents may be resorted to as fallingwithin the scope of the invention.

What is claimed is:
 1. A computer-implemented method to manage capacityof a database system, wherein the database system that includes one ormore database nodes operable to process data associated with a database,wherein the one or more database nodes include one or more physicalprocessors, and wherein the computer-implemented method comprises:configuring the database system to operate at an allotted limitedcapacity below its full capacity to process database queries, byconfiguring at least one of the one or more database nodes to operate atan allotted usage capacity below its full usage capacity to processdatabase queries, wherein an excess capacity in relation to the allottedlimited usage capacity is available to the database system on demand;determining by the one or more physical processors that one or moreproblematic operations associated with the database have occurred,wherein the one or more problematic operations include at least one of:(i) one or more database queries that have been determined to encounteran error during execution, and (ii) execution of one or more databasequeries have been determined not to be optimal; determining by the oneor more physical processors whether to allow excess capacity that isavailable to the database system on demand in relation to the allottedlimited capacity to be used to resolve the problematic operations by atleast performing one or more selected operations pertaining to at leastone of: processing of a selected one or more of the database queriesthat have encountered an error, and optimization of a selected one ormore database queries determined not to be optimal; and when thedetermining determines to allow the excess capacity available to thedatabase system to be used to perform the one or more selectedoperations: allowing by the one or more physical processors the excesscapacity of the database system to be used on demand to perform the oneor more selected operations, by allowing the at least one database nodeto exceed its allotted usage capacity on demand to perform the one ormore operations, not allowing by the one or more physical processors theexcess capacity of the database system to be used to process one or moreof the database queries that have not been selected for least one of:processing of the selected one or more of the database queries that hasencountered an error, and the optimization of the selected one or moreof the database queries.
 2. The computer-implemented method of claim 1,wherein the allowing the access capacity to be used to perform the oneor more selected operations comprises: not allowing at least one or moreoperations associated with the database to use the excess capacity. 3.The computer-implemented method of claim 1, wherein the determiningwhether to allow excess capacity available to the database system to beused to perform one or more selected operations comprises: determiningwhether an error condition has occurred.
 4. The computer-implementedmethod of claim 3, wherein the error condition is associated withscheduling a database query for execution.
 5. The computer-implementedmethod of claim 1, wherein the determining whether to allow excesscapacity available to the database system to be used to perform theselected one or more operations comprises: determining whether tooptimize or further optimize a database query.
 6. Thecomputer-implemented method of claim 1, wherein the determining whetherto allow excess capacity available to the database system to be used toperform the one or more selected operations comprises one or more of thefollowing: (a) identifying an execution plan with an estimatedcompletion time that does meet a goal or a requirement, (b) identifyingan execution plan with an execution time and/or resource consumptiontime that exceed a threshold, and (c) identifying a query with a numberof operations that exceed a threshold.
 7. An apparatus, comprising: oneor more processors operable to: process and store data for a databasesystem configured to operate at a limited capacity below its fullcapacity; configure the database system to operate at an allottedlimited capacity below its full capacity to process database queries, byconfiguring at least one of the one or more database nodes of thedatabase system to operate at an allotted usage capacity below its fullusage capacity to process database queries, wherein an excess capacityin relation to the allotted limited usage capacity is available to thedatabase system on demand; determine that one or more problematicoperations associated with the database have occurred, wherein the oneor more problematic operations associated with the database include atleast one of: (i) one or more database queries that have been determinedto encounter and error, and (ii) execution of one or more databasequeries determined not to be optimal; determine whether to allow excesscapacity available to the database on demand to be used to resolve oneor more problematic operations associated with the database; allow theexcess capacity to be used on demand to resolve the one or moreproblematic operations when the determining determines to allow theexcess capacity available to the database system to be used on demand toperform the one or more operations associated with the database; and notallowing the excess capacity to be used to perform one or more otheroperations associated with the database that are determined not beproblematic.
 8. The apparatus of claim 7, wherein the one or moreoperations pertain to processing a database query that has encounteredan error.
 9. The apparatus of claim 7, wherein the one or moreoperations pertain to optimization of a database query.
 10. Theapparatus of claim 7, wherein the allowing the access capacity to beused to perform the one or more operations only allows the excesscapacity to be used to perform the one or more operations.
 11. Theapparatus of claim 7, wherein the allowing the access capacity to beused to perform the one or more operations comprises: not allowing atleast one or more operations associated with the database to use theexcess capacity.
 12. The apparatus of claim 7, wherein the determiningwhether to allow excess capacity available to the database system to beused to perform one or more operations comprises: determining whether anerror condition has occurred.
 13. The apparatus of claim 12, wherein theerror condition is associated with scheduling a database query forexecution.
 14. The apparatus of claim 7, wherein the determining whetherto allow excess capacity available to the database system to be used toperform one or more operations comprises: determining whether tooptimize or further optimize a database query.
 15. A non-transitorycomputer readable storage medium storing at least executable computercode for managing capacity of a database system that includes one ormore database nodes operable to process data associated with a database,wherein the database system is configured to operate at a limitedcapacity below its full capacity, and wherein the non-transient computerreadable storage medium includes: executable computer code operable toconfigure the database system to operate at an allotted limited capacitybelow its full capacity to process database queries, by configuring atleast one of the one or more database nodes of the database system tooperate at an allotted usage capacity below its full usage capacity toprocess database queries, wherein an excess capacity in relation to theallotted limited usage capacity is available to the database system ondemand; executable computer code operable to determine whether to allowexcess capacity available to the database system on demand to be used toperform one or more problematic operations associated with processing ofthe data by the one or more database nodes, wherein the one or moreoperations associated with the database include: (i) one or moredatabase queries that have been determined to encounter and error, and(ii) optimizations of one or more database queries determined not beoptimal; and executable computer code operable to allow the excesscapacity to be used to perform the one or more problematic operationswhen the determining determines to allow the excess capacity availableto the database system on demand to be used to perform the one or moreproblematic operations associated with processing of the data by the oneor more database nodes; and executable computer code operable not toallow the excess capacity to be used to perform one or more otheroperations associated with the database that are determined not to beproblematic.
 16. The non-transitory computer readable storage medium ofclaim 15, wherein the one or more operations pertain to processing adatabase query that has encountered an error.
 17. The non-transitorycomputer readable storage medium of claim 16, wherein the database queryis selected as a result of scheduling mistake due to a limitation of anestimation technology used to estimate resource usage of the databasequery.
 18. The non-transitory computer readable storage medium of claim15, wherein the one or more operations pertain to optimization of adatabase query.
 19. The non-transitory computer readable storage mediumof claim 18, wherein the database query is a selected database queryrequiring a more extensive and through optimizations than a plurality ofother database queries.